A semi-supervised Chinese-English implicit discourse relationship recognition method and system

A relationship recognition and semi-supervised technology, applied in biological neural network models, semantic analysis, neural architecture, etc., can solve the problems of limiting the performance of Chinese and English implicit discourse relationship recognition

Active Publication Date: 2021-09-24
EAST CHINA JIAOTONG UNIVERSITY
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Problems solved by technology

[0005] In view of the above situation, it is necessary to solve the lack of a method for identifying implicit discourse relations in the prior art using manually annotated discourse relationship datasets in both Chinese and English, which limits the identification of Chinese and English implicit discourse relations to a certain extent. The problem of performance improvement

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  • A semi-supervised Chinese-English implicit discourse relationship recognition method and system
  • A semi-supervised Chinese-English implicit discourse relationship recognition method and system
  • A semi-supervised Chinese-English implicit discourse relationship recognition method and system

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[0069] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0070] These and other aspects of embodiments of the invention will become apparent with reference to the following description and drawings. In these descriptions and drawings, some specific implementations of the embodiments of the present invention are specifically disclosed to represent some ways of implementing the principles of the embodiments of the present invention, but it should be understood that the scope of the embodiments of the present invention is not limited by This restriction. On the contrary, the embodiments of the p...

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Abstract

The present invention proposes a semi-supervised Chinese-English implicit discourse relationship recognition method and system, the method comprising the following steps: step 1, data set preparation; step 2, model construction: in the implicit discourse relationship recognition model based on attention mechanism On the basis of , the Chinese implicit discourse relationship recognition model and the English implicit discourse relationship recognition model are constructed respectively; Step 3, unsupervised model training; Step 4, supervised model training; Step 5, prediction result output. The semi-supervised Chinese-English implicit discourse relationship recognition method proposed by the present invention is based on a large number of unlabeled discourse relationship data sets in two languages ​​and a small amount of manually labeled discourse relationship data sets to jointly train Chinese and English implicit discourse relationship recognition models, The unlabeled and labeled datasets in both languages ​​can be fully and effectively utilized to simultaneously improve the performance of Chinese and English implicit discourse relationship recognition.

Description

technical field [0001] The invention relates to the technical field of computer language processing, in particular to a semi-supervised Chinese-English implicit discourse relationship recognition method and system. Background technique [0002] Implicit discourse relation recognition aims to automatically infer semantic relations between two arguments (sentences or clauses) that lack discourse connectives, e.g., transition and causality. In different languages, there are usually a small number of human-annotated textual relationship datasets, for example, the Chinese CDTB dataset and the English PDTB dataset. Since it is very difficult to manually label chapter relational datasets, the scale of both the CDTB dataset and the PDTB dataset is relatively small. Among them, there are about 5,500 instances of implicit discourse relations marked in the CDTB dataset, while the current largest PDTB dataset only contains about 16,000 instances. Although these manually annotated corp...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F40/30G06F40/42G06N3/04
CPCG06F40/30G06F40/42G06N3/044
Inventor 邬昌兴胡明昆俞亮
Owner EAST CHINA JIAOTONG UNIVERSITY
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